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The Stanford Natural Language Processing Group |
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This is a Java implementation of a maximum entropy classifier, as described in:
Christopher Manning and Dan Klein. 2003. Optimization, Maxent Models, and Conditional Estimation without Magic. Tutorial at HLT-NAACL 2003 and ACL 2003. [pdf slides] [pdf handouts]Maximum entropy models are otherwise known as conditional loglinear models, and are essentially equivalent to multiclass logistic regression models (though parameterized slightly differently, in a way that is advantageous with sparse explanatory feature vectors). classification (a.k.a., maximum entropy models)
The software requires requires Java (JDK1.5+). It is licensed for research and non-commercial use under the GPL. Source is included.
The download is a 1.3m gzipped tar file. If you unpack that file,
you should have everything needed, including example files and documentation.
Start by reading the README.txt file.
Send any questions or feedback to
java-nlp-support@lists.stanford.edu.
Version 1.0 2003-05-26 Initial release
Version 2.0 2007-08-15 New command line interface, substantial increase in options and features (updated on 2007-09-28 with a bug fix)
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